Long-term volcanic hazard assessment on El Hierro (Canary ... · 1854 L. Becerril et al.: Long-term volcanic hazard assessment on El Hierro (Canary Islands) long-term assessment is

Nat. Hazards Earth Syst. Sci., 14, 1853–1870, 2014www.nat-hazards-earth-syst-sci.net/14/1853/2014/doi:10.5194/nhess-14-1853-2014© Author(s) 2014. CC Attribution 3.0 License.

Long-term volcanic hazard assessment on El Hierro(Canary Islands)

L. Becerril 1, S. Bartolini1, R. Sobradelo1, J. Martí 1, J. M. Morales2, and I. Galindo2

1Institute of Earth Sciences Jaume Almera, ICTJA-CSIC, Group of Volcanology, SIMGEO (UB-CSIC) Lluis Sole i Sabariss/n, 08028 Barcelona, Spain2Instituto Geológico y Minero de España (IGME) c/Alonso Alvarado, 43-2A, 35003 Las Palmas de Gran Canaria, Spain

Correspondence to:L. Becerril ([email protected])

Received: 22 January 2014 – Published in Nat. Hazards Earth Syst. Sci. Discuss.: 24 February 2014Revised: 10 June 2014 – Accepted: 13 June 2014 – Published: 28 July 2014

Abstract. Long-term hazard assessment, one of the bastionsof risk-mitigation programs, is required for land-use plan-ning and for developing emergency plans. To ensure qualityand representative results, long-term volcanic hazard assess-ment requires several sequential steps to be completed, whichinclude the compilation of geological and volcanological in-formation, the characterisation of past eruptions, spatial andtemporal probabilistic studies, and the simulation of differenteruptive scenarios. Despite being a densely populated activevolcanic region that receives millions of visitors per year, nosystematic hazard assessment has ever been conducted on theCanary Islands. In this paper we focus our attention on ElHierro, the youngest of the Canary Islands and the most re-cently affected by an eruption. We analyse the past eruptiveactivity to determine the spatial and temporal probability, andlikely style of a future eruption on the island, i.e. the where,when and how. By studying the past eruptive behaviour of theisland and assuming that future eruptive patterns will be simi-lar, we aim to identify the most likely volcanic scenarios andcorresponding hazards, which include lava flows, pyroclas-tic fallout and pyroclastic density currents (PDCs). Finally,we estimate their probability of occurrence. The end result,through the combination of the most probable scenarios (lavaflows, pyroclastic density currents and ashfall), is the firstqualitative integrated volcanic hazard map of the island.

1 Introduction

The possibility of future eruptive activity, coupled with pop-ulation growth and economic and cultural development in themajority of active volcanic areas, means that mitigative mea-sures against volcanic risk, such as the development of vol-canic hazard analyses, must be undertaken. These types ofanalyses are a fundamental part of risk management tasksthat include the developing of volcanic hazard maps, land-use planning and emergency plans.

The volcanic hazard of a given area is the probability thatit will be affected by a process of a certain volcanic magni-tude within a specific time interval (Fournier d’Albe, 1979).Therefore, volcanic hazard assessment must necessarily bebased on good knowledge of the past eruptive history of thevolcanic area, which will tell us “how” eruptions have oc-curred. It also requires the spatial probability of occurrenceof a hazard to be determined; i.e. “where” the next eruptioncan take place (volcanic susceptibility) and its extent, as wellas its temporal probability, in other words “when” the nexteruption may occur in the near future.

The complexity of any volcanic system and its associatederuptive processes, together with the lack of data that is typ-ical of so many active volcanoes and volcanic areas (and inparticular those with long periods between eruptions), makevolcanic hazard quantification a challenge. Long-term hazardassessment is necessary to know how the next eruption couldbe. It is based on the past history of the volcano and the in-formation needed comes from the geological record. Unlikeshort-term assessment that evaluates hazards from days to afew months, using data provided by monitoring networks,

Published by Copernicus Publications on behalf of the European Geosciences Union.

1854 L. Becerril et al.: Long-term volcanic hazard assessment on El Hierro (Canary Islands)

long-term assessment is estimated from years to decades,where the main source of information is mainly structuraldata from past eruptions (Marzocchi et al., 2006). Differ-ent steps need to be followed sequentially in any long-termvolcanic hazard assessment. The first step consists of eval-uating the likelihood of a future eruption, which will pro-vide an indication of which areas are most likely to hostfuture vents (Martí and Felpeto, 2010). The long-term spa-tial probability of vent opening can be estimated using struc-tural data such as vents, dykes, faults, fractures and eruptivefissure-alignments obtained from geological and geophysicalstudies. These data can be converted into Probability Den-sity Functions (PDFs) and then combined to obtain the fi-nal susceptibility map (Martin et al., 2004; Felpeto et al.,2007; Connor and Connor, 2009; Martí and Felpeto, 2010;Cappello et al., 2012; Bartolini et al., 2013; Becerril et al.,2013). Susceptibility maps show the spatial probability ofhosting new future eruptions. This term has been commonlyused during the last years by other authors in the volcanicfield (Felpeto et al., 2007; Cappello et al., 2010, 2011, 2012;Martí and Felpeto, 2010; Vicari et al., 2011; Alcorn et al.,2013; Bartolini et al., 2013; Becerril et al., 2013).

The next step corresponds to the temporal probability es-timation of any possible volcanic event. Long-term forecast-ing is based on historical and geological data, as well as ontheoretical models, and refers to the time window availablebefore an unrest episode occurs in the volcanic system. Inthis regard, some authors use probabilistic statistical meth-ods based on the Bayesian event tree for long-term volcanichazard assessment (Newhall and Hoblitt, 2002; Marzocchiet al., 2008; Sobradelo and Martí, 2010), while some othersuse a deterministic approach (Voight and Cornelius, 1991;Kilburn, 2003; see also Hill et al., 2001).

Once spatial and temporal probabilities have been esti-mated, the next step forward consists of computing severalscenarios as a means of evaluating the potential extent ofthe main expected volcanic and associated hazards. Mostof these studies are based on the use of simulation modelsand Geographical Information Systems (GIS) that allow vol-canic hazards such as lava flows, PDCs and ash fallout to bemodelled and visualised (Pareschi et al., 2000; Felpeto et al.,2007; Toyos et al., 2007; Crisci et al., 2008; Cappello et al.,2012; Martí et al., 2012; Alcorn et al., 2013).

All of these steps should be undertaken to evaluate thepotential volcanic hazards of any active volcanic area. Sim-ilar approaches have been applied in volcanic areas suchas Auckland, New Zealand (Bebbington and Cronin, 2011);Etna, Sicily (Cappello et al., 2013); and Tenerife, Spain(Martí et al., 2012); Perú (Sandri et al., 2014). Nevertheless,other procedures have also been applied in order to assessvolcanic hazards in Campi Flegrei, Italy (Lirer et al., 2001);Furnas (São Miguel, Azores) Vesuvius in Italy (Chester etal., 2002); and Auckland, New Zealand (Sandri et al., 2012).Compared with these previous approaches, our study of-fers a procedure that facilitates undertaking volcanic hazard

assessment in a systematic way, which can be easily appliedto other volcanic areas around the world.

The Canary Islands are the only area of Spain in whichvolcanic activity has occurred in the last 600 years, repre-senting one of the world’s largest oceanic volcanic zones.The geodynamic environment in which the archipelago liesand the characteristics of its recent and historical volcan-ism suggest that the volcanic activity that has characterisedthis archipelago for more than 60 Ma will continue in the fu-ture. Previous volcanic hazard studies conducted on the Ca-nary Islands have not followed a systematic method. Mostwork to date has focused on Tenerife and Lanzarote (Gómez-Fernández, 1996; Araña et al., 2000; Felpeto et al., 2001,2007; Felpeto, 2002; Carracedo et al., 2004a, b, 2005; Martíand Felpeto, 2010; Sobradelo and Martí, 2010; Martí et al.,2012; Bartolini et al., 2013), although other studies have beencarried out on Gran Canaria (Rodríguez-González, 2009), ElHierro (Becerril et al., 2013) and one for the Canary Islandsas a whole (Sobradelo et al., 2011).

In this study we focus on El Hierro and conduct a long-term volcanic hazard assessment by taking into account spa-tial and temporal probabilities. Despite being small and sub-marine in nature (Martí et al., 2013), the most recent erup-tion on El Hierro (October 2011–February 2012) highlightedthe need for volcanic hazard studies, given the negative im-pact on tourism and the local economy of any volcanic event.Although this eruption was not different in terms of magmavolume and volcanic products from most eruptions that his-torically occurred in the Canarian Archipelago, this eruptionmarked the end of a 40-year period of quiescence in this vol-canic region. El Hierro has a population of 10 960 inhabitants(www.ine.es), or 0.51 % of the total population of the CanaryIslands. Its main economic resources are tourism and fishery,two aspects that may be – and in fact were – seriously af-fected by the impact of volcanic activity.

In this work we present a systematic analysis of the vol-canic hazards present on this island that includes the fol-lowing steps: (1) characterisation of past volcanism in thestudy area; (2) estimation of spatio-temporal probabilities;(3) simulation of the most probable eruptive scenarios suchas lava flows, pyroclastic fallout and pyroclastic density cur-rents (PDCs); and (4) assessment of the volcanic hazard.

2 Geological setting

The Canary Islands extend for roughly 500 km in a chainthat has developed on the passive margin of the Africanplate in the eastern central Atlantic Ocean (Fig. 1, inset).The Canarian Archipelago is the result of long-term volcanicand tectonic activity that started around 60 Ma (Robertsonand Stillman, 1979; Le Bas et al., 1986; Araña and Ortiz,1991; Marinoni and Pasquaré, 1994). A number of contrast-ing models – including the presence of a hotspot, the prop-agation of a fracture from the Atlas Mountains and mantle

Nat. Hazards Earth Syst. Sci., 14, 1853–1870, 2014 www.nat-hazards-earth-syst-sci.net/14/1853/2014/

www.ine.es

L. Becerril et al.: Long-term volcanic hazard assessment on El Hierro (Canary Islands) 1855

Figure 1. Geological map of El Hierro Island. At the left top part of the figure, location of the Canary Islands is presented where LZrepresents Lanzarote; FV represents Fuerteventura; GC represents Gran Canaria; TF represents Tenerife; LG represents La Gomera; LPrepresents La Palma; EH represents El Hierro. Timanfaya eruption in Lanzarote has been coloured in red.

decompression melting associated with uplift of tectonicblocks – have been mooted to explain the origin of the Ca-nary Islands (Le-Pichon and Fox, 1971; Anguita and Hernán,1975; Schmincke, 1982; Araña and Ortiz, 1991; Hoernleand Schmincke, 1993; Hoernle et al., 1995; Carracedo et al.,1998; Anguita and Hernán, 2000).

Although all of the islands (except La Gomera) have beenwitness to Holocene volcanic activity, volcanism has histor-ically been restricted to La Palma, Lanzarote, El Hierro andTenerife (Fig. 1, inset). In all cases, historical eruptive activ-ity has produced mafic eruptions ranging in intensity fromHawaiian to violent Strombolian (Valentine and Gregg, 2008and references therein) and have given rise to lavas and sco-ria cones. Typically, the islands’ historical eruptions have oc-curred in active rift zones along eruptive fissures and haveoccasionally generated alignments of cones. Other than thecase of the Timanfaya eruption in 1730 in Lanzarote (Fig. 1,inset), which lasted for 6 years, the duration of eruptions hasranged from a few weeks to a few months. The total vol-ume of erupted magma ranges from 0.01 to> 1.5 km3 (DRE,dense rock equivalent), the upper extreme occurring in thecase of the Timanfaya eruption. In all cases the resulting vol-canic cones were constructed during single eruptive episodes(i.e. they should be referred to as monogenetic) that usuallyinvolved several distinctive phases with no significant tempo-ral separations between them. Monogenetic volcanic fieldsconsist of individual, commonly mafic volcanoes, built insingle, relatively short-lived eruptions. These volcanoes usu-ally take the form of scoria cones, tuff rings, maars or tuff

cones; scoria cones are the most common landform and showa great diversity in size, morphology and eruptive products(Valentine and Gregg, 2008; Kereszturi and Németh, 2012).Individual volcanic edifices are characteristically small involume, typically< 0.1 km3 of DRE, but the eruption canbe complex with many different phases and styles of activ-ity (Németh, 2010). Situated in the southwestern corner ofthe archipelago, El Hierro is the youngest of the Canary Is-lands; its oldest subaerial rocks have been dated at 1.12 Ma(Guillou et al., 1996). It rises from a depth of 4000 m toaround 1500 m a.s.l. and has an estimated total edifice vol-ume of about 5500 km3 (Schminke and Sumita, 2010). It cor-responds to a shield structure formed by different volcanicedifices and includes three rift zones on which recent volcan-ism has been concentrated (Guillou et al., 1996; Carracedo etal., 2001) (Fig. 1). Other relevant morphological features in-clude the collapse scars of El Golfo, Las Playas and El Julan(Fig. 1). The emergent parts of these rifts are characterisedby steep narrow ridges, corresponding to aligned dyke com-plexes with clusters of cinder cones. Pre-historical eruptionshave been recognised on all three rifts on El Hierro (Guillouet al., 1996; Carracedo et al., 2001).

Recent subaerial volcanism on El Hierro is monogeneticand is mostly characterised by the eruption of mafic mag-mas as well as the intrusion of subvolcanic bodies ranging incomposition from picrobasalts to basanites (Pellicer, 1977;Stroncik et al., 2009), which have generally erupted along therift zones. Some felsic dykes and lava flows associated withthe older parts of the island have also been reported (Guillou

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et al., 1996; Carracedo et al., 2001) but are volumetricallysubordinate to the mafic material. In addition, an explosivefelsic eruption has been documented in association with thefinal episodes of the construction of the edifice of El Golfo–Las Playas (later than 158 ka), before it was destroyed bya massive landslide (Pedrazzi et al., 2014). Mafic eruptionstypically occur from fissures, and produce proximal fallout,ballistic ejecta and lava flows. PDC deposits have also beenreported in cases in which eruptions are related to hydromag-matic episodes (Balcells and Gómez, 1997; Pedrazzi et al.,2014).

The erupted volume of magma in eruptions on El Hierrotypically ranges from less than 0.0001 to 0.1 km3 (DRE),values that are of the same order as most of the other his-torical eruptions on the Canaries (Sobradelo et al., 2011).One of the most important eruptive episodes in the last fewthousand years on El Hierro was the Tanganasoga eruption(Fig. 1), which occurred inside the depression of El Golfoalong a N–S-oriented fissure, at most 20 ka (Carracedo etal., 2001). Several cones and emission centres formed, giv-ing rise to one of the largest volcanic edifices on the islandvia the accumulation of ankaramitic lavas and pyroclastic de-posits (Carracedo et al., 2001) (Fig. 1). In addition to the sub-aerial volcanism, bathymetric studies (Gee et al., 2001) haverevealed that a significant number of well-preserved volcaniccones exist on the submarine flanks of the island, in partic-ular on the continuation of the southern rift, which suggeststhat significant submarine volcanic activity has also occurredrecently. As a confirmation of this observation, a submarineeruption occurred from 10 October 2011 to the end of Febru-ary 2012 on the southern rift zone, 2 km off the coast of ElHierro (Martí et al., 2013).

3 Methods

The spatial probabilities of hosting new vents were estimatedusing the study by Becerril et al. (2013) of volcanic sus-ceptibility on El Hierro, which takes into account most ofthe structural data (vents, eruptive fissures, dykes and faults)available from the island. The temporal part of the long-term volcanic hazard assessment was carried out with theBayesian-event tree-based software HASSET (Sobradelo etal., 2014a) using geochronological data for El Hierro and his-torical data from the whole archipelago. Hazard scenarios oflava flows, fallout and PDCs were obtained with the VORIStool (Felpeto et al., 2007) since they are the most likely vol-canic scenarios on the island. The data collection required foreach hazard assessment was divided into three parts (spatial,temporal, and scenarios), according to the use made of eachdata set.

4 How: characterisation of the eruptions

The characterisation of past volcanic eruptions – typicallybased on the determination of eruptive parameters derivedfrom the study of erupted products found in the geologicalrecords – is crucial for understanding past eruptive behaviourand for forecasting future volcanic activity.

Recent volcanic activity on El Hierro is largely charac-terised by monogenetic mafic volcanism and the building ofmore than 220 cones, most of which are scoria cones thatcorrespond to the most recent eruptive cycle (rift volcanism).

Hawaiian and Strombolian activity are the most commoneruptive styles observed on the island (Becerril, 2009), whichhave formed extensive lava flow fields, spatter and cindercones made of scoria agglutinates and well-bedded lapilliscoria and ash, respectively. Violent Strombolian activity– refereeing to explosive activity that produces sustainederuption columns up to∼ 10 km high (without reaching thetropopause) and with the dominant clast sizes being ash tolapilli (Valentine, 1998; Arrighi et al., 2001; Valentine andGregg, 2008) – has been also recognised through the pres-ence of several distal ash deposits on the geological recordof the island. Phreatomagmatic episodes generating rhyth-mic laminated sequences of coarse juvenile ash and lapilli-rich beds with accidental lithic fragments also occurred atthe interior of the island but in less frequency than thosementioned above. In addition, some hydromagmatic erup-tions occurred along the coast, producing tuff ring depositson the western part of the island (Becerril, 2009). Eruptionsrelated to felsic magmas and producing either trachytic lavaflows (Guillou et al., 1996) or trachytic pyroclastic deposits(Pellicer, 1977; Balcells and Gómez, 1997) have also beendescribed. In this sense, it is remarkable that the occurrenceof a base-surge-type explosive eruption that generated di-lute pyroclastic surge deposits covering an area of more than15 km2 around the Malpaso area (Fig. 1) (Pedrazzi et al.,2014).

We also took into account the final constructive cycle(158 ka–present) of the island to characterise of the size ofthe eruptions. The volume of the cones was calculated us-ing ARCGIS 10.0 (ESRI©) through the analysis of a dig-ital elevation model (DEM), subtracting the current DEMtopography to the restored paleo-topography. The volumeof lava flows and distal pyroclastic deposits was calculatedtaking into account their areal extent and thickness vari-ations. This provided a first-order estimate of the eruptedvolume, despite the lack of a precise paleo-topography. Interms of the total volume of erupted material, the largesteruptions that occurred during the final growing cycle onEl Hierro correspond to volumes of the order of 0.15–0.042 km3 (Tanganasoga, Mt. del Tesoro, the latter was cal-culated by Rodríguez-González et al., 2012). A minimumvalue is for Mt. Los Cascajos, with just 0.0016 km3. The vol-canic explosivity index (VEI) (Newhall and Self, 1982) anddense rock equivalent (DRE) derived from the volumetric



data of the eruptions were also calculated. Most of VEIvalues are in the range of 0–2, whilst the erupted volumeof magma (using mean magma density of 2.8 g cm−3, an av-erage rock density of 2.44 g cm−3 obtained from laboratoryanalysis of El Hierro samples, and applying the equation:DRE (km3) = volume of volcanic deposit (km3) × densityof volcanic deposit (kg m−3)/magma density (kg m−3)) formost of the recent eruptions on El Hierro lies within therange of 0.0001–0.1 km3 (DRE). The DRE calculation wasbased on the volume of exposed materials (lavas and py-roclastic deposits) so our total volumes are minimum esti-mates, but similar to those assigned to other monogeneticfields, which normally have volumes between 0.0001 and afew cubic kilometres for individual eruptions (e.g. Kereszturiet al., 2013). For example, the erupted volume of magma onthe Canary Islands typically ranges from 0.001 to 0.2 km3

(DRE) (Sobradelo et al., 2011). In the Garrotxa volcanic field(Spain) the total volume of extruded magma in each erup-tion ranges from 0.01 to 0.2 km3 (DRE) (Bolós et al., 2014).The volumes of basaltic eruptions on Terceira (Açores, Por-tugal) range in size from 0.1 km3 to less than 0.001 km3

(DRE) (Self, 1976). In the case of Auckland (New Zealand),monogenetic field volumes are in the range of 0.00007 to0.698 km3 (Kereszturi et al., 2013).

By comparing pre- and post-eruption high-resolutionbathymetries, the total bulk volume erupted during the sub-marine eruption of 2011–2013 was estimated at 0.33 km3

(Rivera et al., 2013).Most of the lava flows on El Hierro that were emplaced

from cones located on and off the rift zones reached the sea.Therefore, it was not possible to measure precisely the max-imum lengths of past lava flows. Nevertheless, the Mt. delTomillar (Fig. 1) lava flow, which did not reach the sea,has a total length of 8 km. However, for further simulations(Sect. 6.1) we considered this value as a minimum length forthe lava flows and used 15 km as a more reliable length. Themean thickness of lava flows was obtained from the averagevalue (3 m) of individual flows measured in the field.

5 Where: spatial analysis

An essential step in obtaining a volcanic hazard map is todetermine the most likely areas to host new eruption vents,a task based on the drawing of susceptibility maps basedon geological, structural and geophysical data (Martí andFelpeto, 2010). Structural elements such as vents, eruptivefissures, dykes and faults are used to pinpoint areas wherenext eruptions may most likely occur. A volcanic suscepti-bility map shows the spatial distribution of vent opening forfuture eruption and represents the basis for further temporaland spatial probability analysis and the definition of erup-tive scenarios. We used the susceptibility map developed byBecerril et al. (2013) following the methodology employedby Cappello et al. (2012) (Fig. 2). This map is based on the

Figure 2.Onshore spatial probability distribution of future volcaniceruptions map of El Hierro Island, showing the divisions of the sec-tors. Modified from Becerril et al. (2013).

five data sets representing the volcano-structural elements onEl Hierro: (1) subaerial vents and eruptive fissures pertainingto the island’s rift volcanism, which include sub-recent andrecent eruptions; (2) submarine vents and eruptive fissures in-ferred from bathymetric data; (3) eruptive fissures and emis-sion centres identified on the Tiñor and El Golfo–Las Playasedifices; (4) presence of dykes; (5) and presence of faults.

To carry out this spatial assessment, we subdivided thespatial probability map into 5 sectors (Fig. 2) based on sus-ceptibility values, topographic constraints and expected haz-ards. First, we differentiated the subaerial and the submarinearea, taking into account differences in the expected hazards.After that, the emergent part of the island was subdivided ac-cording to areas with different structural controls (differentstrike of the volcano-structures as dykes and fissures), differ-ent topographical constrains (zones 1, 3 and 4 represent riftareas, while zone 2 is an embayment), and different suscep-tibility values according to the map developed by Becerril etal. (2013). This map enables us to select the areas with thegreatest likelihood of hosting future scenarios.

6 When: temporal analysis

Temporal analyses were performed using HASSET(Sobradelo et al., 2014a) a Bayesian event tree structurewith eight nodes representing different steps to evaluatethe temporal probability and evolving from a more generalnode of unrest to the more specific node of the extent of thehazard (Sobradelo and Martí, 2010).

We based the study of temporal probability on the cata-logue of eruptions documented in Table 1. In all, 25 eruptionsare documented from the last 158 ka, data confirmed by therelative stratigraphy established during our field work. Six of



Table 1.The principal characteristics of the eruptions identified during the last constructive episode of El Hierro. The eruptions included inthis table are those for which geochronological data exist and that are consistent with the field-relative stratigraphy established in this study.In addition to the geochronological data and the corresponding references, the rest of the information included in the table corresponds toinformation related to the first nodes in the HASSET (Sobradelo et al., 2014a) event tree used in this study. See text for more details.

ID Unrest Origin Outcome Location Composition Hazard Extent Reference

1 2011 magmatic magmatic 5 Mafic lava flow medium Martí et al.eruption (2013)

2 1793 seismic no eruption ? HernándezPacheco (1982)

3 2500± 70 (BP) magmatic magmatic 3a Mafic ballistic+ medium Carracedo eteruption lava flow al. (2001)

4 4230 (BP) magmatic magmatic 3a Mafic ballistic+ short Fúster et al.eruption lava flow (1993)

5 8000± 2000 (BP) magmatic magmatic 1a Mafic ballistic+ short Pérez Torradoeruption lava flow et al. (2011)

6 9000 (BP) magmatic magmatic 3a Mafic ballistic+ medium Rodríguez-Gonzálezeruption lava flow et al. (2012)

7 12 000± 7000 (BP) magmatic magmatic 2a Mafic lava flow short Guillou et al.eruption (1996)


9 15 000± 2000 (BP) magmatic magmatic 4b Mafic lava flow short Carracedo eteruption al. (2001)



12 38 700± 12 600 (BP) magmatic magmatic 2b Mafic lava flow short Longpré et al.eruption (2011)


14 44 000± 3000 (BP) magmatic magmatic 4b Mafic lava flow short Guillou et al.eruption (1996)


16 80 000± 40 000 (BP) magmatic magmatic 3a Felsic lava flow medium– Fúster et al.eruption large (1993)

17 86 600± 8300 (BP) magmatic magmatic 1a Mafic lava flow short Longpré et al.eruption (2011)

18 94 500± 12 600 (BP) magmatic magmatic 4a Mafic lava flow short Longpré et al.eruption (2011)

19 115 300± 6900 (BP) magmatic magmatic 4a Mafic lava flow short Longpré et al.eruption (2011)

20 126 000 magmatic magmatic 5 Mafic lava flow short Klügel et al.eruption (2011)

21 133 000± 200 magmatic magmatic 5 Felsic lava flow short Van dereruption Bogard (2013)

22 134 000 (BP) magmatic magmatic 3a Mafic lava flow short Széréméta eteruption al. (1999)

23 142 000± 2000 (BP) magmatic magmatic 5 Felsic lava flow short Van der Bogarderuption (2013)





these eruptions took place during the previous 11 700 years(Holocene), but only 2 unrest episodes have been docu-mented in the last 600 years (historical period). The informa-tion from these eruptions was used to characterise the pasteruptive activity on El Hierro and to estimate some of theinput parameters required for our hazard assessment.

However, due to the scarcity of dated eruptions and to thecertainty that not all the eruptions that occurred in this pe-riod have been identified and/or dated, we also used in ourtemporal analysis as data for the last 600 years (15th centuryto 2013) the historical data set for the whole of the CanaryIslands (see Sobradelo et al., 2011). Therefore, using HAS-SET we were able to estimate the probability that a volcanicepisode will occur in the forecasting time interval (the next20 years). Given that the data set time window is 600 years,we thus obtained 30 time intervals of data for the study pe-riod. Here we restrict our data set to the historical period,which includes the recent submarine eruption (2011) and theseismic unrest of 1793. The remaining 23 eruptions in thiscatalogue – referred to as pre-historical – will be used to as-sign prior weights to nodes 2 to 8.

7 Input data for HASSET

7.1 Node 1: unrest

This node estimates the temporal probability of a reawak-ening of the system in the next time window by examin-ing the number of past, non-overlapping, equal-length timewindows that encompass an episode of unrest. Implicitly,this node estimates the recurrence time with a Bayesian ap-proach that does not use the time series. It did not take intoaccount the repose period between eruptions or the possi-ble non-stationary nature of the data. However, Sobradelo etal. (2011) used extreme value theory to study the historicalrecurrence of monogenetic volcanism on the Canary Islandssince the first written records appeared at the beginning of the15th century. By modelling the inter-period times with a non-homogeneous generalised Pareto–Poisson distribution, thisstudy estimated as of 2010 that the probability of an erup-tion of a magnitude> 2 anywhere on the Canary Islands inthe next 20 years was 0.97± 0.00024.

In order to compute the probability of having (at least) anunrest episode in the next 20 years, we need two pieces ofinformation: (1) our starting beliefs or weights for each pos-sibility (yes, no) and (2) the number of past events during theperiod of study. As per the number of past events, it showsthat in the last 600 years (historical period), there have beentwo episodes of unrest identified at El Hierro (a seismic un-rest and the latest magmatic unrest in 2011 which resultedin eruption). As per the starting weights for each option, ifwe did not have any information at all we would start withthe state of total ignorance or total epistemic uncertainty, andgive 50/50 chance to each option. However, this is not the

case, as in the study of the volcanic recurrence for the CanaryIslands as of 2010 (based on volcanic records from the is-lands of Tenerife, La Palma and Lanzarote) (Sobradelo et al.,2011), there is an estimated 97 % probability of at least oneeruption in the next 20 years, anywhere on the Canary Islands(including El Hierro). Therefore, rather than starting with a50/50 chance, this study allowed us to assign our a priori be-liefs for the “unrest” node in the island of El Hierro (yes = 97,no = 3), and then we used the 2 historical episodes of unrestdocumented in El Hierro to update those initial beliefs.

The reason why we used the 2 historical events in the cat-alogue of El Hierro, and not the remaining 23 pre-historicalevents, was to avoid misleading results in the probability ofunrest. If we had used the entire catalogue we would havesaid to the model that there was on average 1 eruption every7900 years (158 000/20), which is not realistic, as the cat-alogue is incomplete. For that reason we updated our priorbeliefs with the historical part of the catalogue that we weremost confident with. Given our confidence in these results,we were able to assign an epistemic uncertainty of 50 to ourdata weights, which means that new evidence regarding inter-vals with non-eruptive behaviour will not significantly mod-ify our prior assumptions. As shown by the posterior proba-bilities in column 6 of Table 2, despite 28 intervals out of 30(600 years/20 estimated time intervals) with no unrest, theposterior probability of unrest in the next 20 years is still sig-nificantly large.

7.2 Node 2: origin

We considered four types of unrest that could occur on ElHierro: magmatic, geothermal, seismic and others. In spiteof the predominant magmatic and seismic behaviour in pastactivity, we cannot exclude either geothermal activity or falseunrest. In fact, hydromagmatic deposits exist in the interior ofthe island that were most probably associated with the pres-ence of shallow aquifers. Some of these deposits also containhydrothermally altered lithic clasts, which also suggest theexistence of localised hydrothermal systems. Thus, it was im-possible to rule out the possibility of geothermal unrest. Falseunrest can occur when non-volcanic signals are recorded to-gether with volcanic signals. For example, changes in thegravity field, ground deformation or even seismicity unre-lated to any volcanic activity could be associated with vari-ations in the recharge and/or extraction of meteoric waterinto/from aquifers in El Hierro. Even so, we still believe thatin monogenetic volcanism magmatic changes are the mainsource of unrest and so we gave the greatest weight to mag-matic unrest (0.96) and split the rest evenly among the otheroptions. The prior weights were assigned on the basis of apriori beliefs and so we allocated a value of 10 to the epis-temic uncertainty since we still expect the majority of unrestto be of magmatic origin. However, it is still important to givemore weight to new evidence.



Table 2.Input data for HASSET (columns 1 to 5) and output probability vectors and standard deviations (columns 6 and 7). Prior weights anddata weights are estimated using pre-historical data, a priori beliefs and published studies on global volcanic unrest during the last century.Past data are based on the eruptions recorded in the last 600 years, considered as the historical period for the Canary Islands.

Node Event Past Prior Data Probability Standardname data weight weight estimate deviation

Unrest Yes 2 0.97 50 0.64 0.07Unrest No 28 0.03 50 0.36 0.07Origin Magmatic 1 0.94 10 0.88 0.09Origin Geothermal 0 0.02 10 0.02 0.03Origin Seismic 1 0.02 10 0.08 0.07Origin Other 0 0.02 10 0.02 0.03Outcome Magmatic eruption 1 0.64 10 0.62 0.13Outcome Sector failure 0 0.12 10 0.10 0.08Outcome Phreatic explosion 0 0.12 10 0.10 0.08Outcome No eruption 1 0.12 10 0.17 0.10Location Zone 1 1 0.16 50 0.17 0.05Location Zone 2 0 0.07 50 0.07 0.03Location Zone 3 0 0.29 50 0.28 0.06Location Zone 4 0 0.16 50 0.15 0.05Location Zone 5 1 0.32 50 0.33 0.06Composition Mafic 1 0.87 10 0.88 0.09Composition Felsic 0 0.13 10 0.12 0.09Size VEI 1− 0 0.31 1 0.25 0.19Size VEI 2 1 0.62 1 0.70 0.21Size VEI 3+ 0 0.07 1 0.06 0.10Size n.a. 0 0 0 0.00 0.00Hazard Ballistic 1 0.12 10 0.15 0.09Hazard Fallout 1 0.05 10 0.09 0.07Hazard PDC 0 0.03 10 0.03 0.04Hazard Lava flow 1 0.8 10 0.73 0.11Hazard Lahars 0 0 0 0.00 0.00Hazard Debris avalanche 0 0 0 0.00 0.00Hazard Other 0 0 0 0.00 0.00Extent Short 0 0.87 10 0.80 0.11Extent Medium 1 0.09 10 0.16 0.10Extent Large 0 0.04 10 0.04 0.05

7.3 Node 3: outcome

A study of global volcanic unrest in the 21st century(Phillipson et al., 2013) shows that 64 % of unrest episodeslead to eruptions. On the other hand, in light of previousstudies on El Hierro (Carracedo et al., 2001; Pedrazzi et al.,2014), we were unable to rule out the possibility that, asidefrom a magmatic eruption, a sector failure or a phreatic ex-plosion might also follow on from an episode of unrest.

Therefore, we assigned a weight of 0.64 to the magmaticeruption and split the remaining 0.36 evenly between the al-ternative nodes. As these weights were assigned based ongeneral studies and a priori beliefs that did not necessar-ily include data from El Hierro, we gave a value of 10 tothe epistemic uncertainty. As with the previous node, wedid not give a total epistemic uncertainty, as we still believethat the largest weight should be for the magmatic eruptionbranch; however, we still want new evidence to be able to

contribute significantly to updating our prior weights. Thetwo data points in our historical catalogue already include anepisode of unrest that did not evolve into an eruption and sowe should expect the prior weight of 0.12 assigned to the “Noeruption” node to be substantially increased after the new ev-idence is entered in the model and the posterior probabilitiesare computed (Table 2, column 6).

7.4 Node 4: location

We divided the island into 5 zones and 11 subzones to beable to perform a volcanic hazard assessment of El Hierrobased on the past geological information described above(Fig. 3). These five main zones were established accordingto the structural (susceptibility) and topographic character-istics of the island, whilst the subdivisions were made bytaking into account the potential occurrence of hydrovol-canic episodes. Thus, subzones 1b–4b represent areas that



Figure 3. Sectors and subsectors defined on El Hierro. Sectors 1–4show onshore division while sector 5 represents the offshore area.The division is based on differences in structural patterns, spatialprobability of hosting new vents and expected hazards. Subsec-tors a–c take into account the potential occurrence of hydrovolcanicepisodes.

could include the focus of and/or be affected by hydrovol-canic episodes caused by the interaction of seawater with theerupting magma. Given the data, regarding such episodes inthe past geological record, we considered that the offshorezone between the bathymetric line of 200 m and the onshorearea near the coast, which already includes several hydrovol-canic edifices, was suitable for the occurrence of such pro-cesses (Fig. 3). Moreover, subzones 3c and 4c in the interiorof the island provide evidence of phreatomagmatic eruptionsin the past.

The susceptibility analysis of the island, based on the studyby Becerril et al. (2013) (Fig. 2), allowed us to assign theprior weights to each node with a high degree of confidence,as shown in Table 2. The reliability of the susceptibility mapenables us to assign a data weight of 50 (since the priorweights were estimated using past data from El Hierro) ac-counting for the uncertainties in the data catalogue. For thisreason, we felt very confident in the initial distribution ofthe prior weights and any new evidence is likely to confirmthem. Of the two historical events, one was in zone 5 (2011–2012 eruption). This unrest lasted 4 months before leading toan eruption which was fully monitored by the Instituto Ge-ográfico Nacional (López et al., 2012).The other one refersto the 1793 seismic unrest whose location is uncertain, al-though historical documents describe it as being in the north-west submarine area, i.e. zone 5.

7.5 Node 5: composition

From the pre-historical set of 23 eruptions shown in Table 1,87 % correspond to mafic events and 13 % to felsic events.

As we were aware of the incompleteness of the data cata-logue, especially in the oldest part, we were not confident ifthis was indeed the proportion for the composition of priorweights. Some – or many – felsic eruptions may not be doc-umented for example, the Malpaso member, a felsic explo-sive eruption, has been identified on the upper part of ElGolfo–Las Playas volcano (Pedrazzi et al., 2014) but wasnot included in our catalogue because we lack a precise date.The prior weights are not random, as they are based on well-documented data. For this reason, we assigned an epistemicuncertainty of 10 to our data weights so that if new evidencearrives, these prior values are still accounted for (but more soif there is new evidence), thereby ensuring that any new datawill contribute significantly to updating our prior beliefs.

7.6 Node 6: size

The erupted volume of magma on the Canary Islands typ-ically ranges from 0.001–0.2 km3 (DRE) (Sobradelo et al.,2011). Due to a lack of accurate volume data, we assumedthat volume values on El Hierro were of the same orderas in most of the historical eruptions in the Canaries. Thelast eruption (2011–2012) was characterised by lava flows ofmedium extent with VEI 2 and so, by using this information,we were able to assign the weights for VEI 1, VEI 2 andVEI 3, as 0.31, 0.62 and 0.07, respectively.

In the particular case of El Hierro, we observed cases ofhydrovolcanic episodes associated with PDC. This wouldimply VEI sizes that are greater than those on which theseprior weights are estimated. Furthermore, the data docu-mented in Sobradelo et al. (2011) is based on Magnitudesize, as there was not enough information to estimate thecorresponding VEI. For this reason and owing to the lack ofmagnitude information for the catalogue of eruptions on ElHierro, we were not confident of the prior weights assignedand so an epistemic uncertainty value of 1 was the most ap-propriate, and would also ensure that if new evidence arrivesfor different sectors, it will contribute significantly to updat-ing our prior knowledge. In this way, we gave more weightto the new evidence than to our prior beliefs.

7.7 Node 7: hazard

Based on past activity, possible eruption products includeballistic ejecta, fallout, PDCs and lava flows with the priorweights shown in Table 2, computed using the 23 pre-historiceruptions in Table 1. Most mafic eruptions generated lavaflows and proximal fallout. However, a revision of the de-posits generated from past volcanic events also reveals thatsome eruptions located close to the coastline correspond tohydrovolcanic episodes generating PDC deposits. In a sim-ilar way, some of the hydrovolcanic deposits found on landnear the coast in fact originated from very shallow subma-rine eruptions. Thus, there is reason to include in subzone b(Fig. 3) both coastal and offshore zones to a maximum depth



of 200 m, based on the assumption that vents located in thesesubzones could generate hydrovolcanic phases and producePDCs.

Of all the possible hazard products, we were confident thatballistic ejecta, fallout, PDCs and lava flows could occur andso we gave zero weight to the remaining options (lahar, de-bris avalanche and others). However, for the same reasonsgiven for the composition weights (felsic vs. mafic), we as-signed a value of 10 to the epistemic uncertainties, as thesedata weights could change if we had a more complete datacatalogue; however, they are still not completely uninforma-tive, as they are based on past records. In this way, we ensurethat new evidence will be well accounted for in new updatesand that prior weights are not fully dropped when this newevidence arrives.

7.8 Node 8: extent

Extent refers to the distance reached by eruption products(lava flows, ballistic ejecta, fallout and PDCs) from erup-tion points that can be deduced from the geological record.The extent of products from the eruptions documented onEl Hierro is comparable to those on the rest of the CanaryIslands. We considered small distances for those short lavaflows that reach up to 5 km, medium distances (5–15 km) forPDC deposits, ballistics and lava flows that reach the sea,and large extent mainly for fall out deposits that can expandmore than 15 km. As with the previous node, on the basisof data from the oldest eruptions (Table 1), 87 % of extentsare small, while 9 % are medium and 4 % large. We assigneda positive weight to a scenario that gives rise to a large ex-tent of products that will account for the potentially moreexplosive eruptions seen in the geological record that relateto felsic eruptions or even hydromagmatic eruptions. For thesame reasons given for the previous node, we assigned anepistemic value of 10 to all branches.

8 Results

Columns 6 and 7 in Table 2 show the output from HASSET.Although we started with 28 time windows with no unrest,the posterior probability of unrest in the next 20 years is sig-nificantly large (64 %; 36 % for no unrest), due to the highvalue of the data weight. The same effect occurs with thenode location, in which the posterior probabilities remain inthe same proportion as the prior weights. The episode of seis-mic unrest in 1793 has updated our prior beliefs from 2 to8 %, given that we assigned low confidence levels to the ini-tial values. In general, comparing columns 4 and 6 in Table 2,we can see how past data can significantly change the priorprobabilities for which we assumed low confidence (10 orless – large epistemic uncertainty), while prior weights as-signed with high confidence remain consistent after new ev-idence is entered in the model.

Looking at the different scenarios (as a combination ofthe first nodes and branches up to node location) (Table 3a),we see that the 5 most likely scenarios are a basaltic erup-tion with magmatic unrest in zones 5, 3, 1, 4 and 2 (inthat order) with probabilities of occurrence over the next 20years of 0.11± 0.04, 0.10± 0.03, 0.06± 0.02, 0.05± 0.02and 0.02± 0.01, respectively, for any VEI and any type ofhazard or extent. However, although some of these estimateshave a large standard deviation due to sizeable uncertaintiesin the input data, they are consistent with observations fromthe past. Thus, using the information in the data catalogue,we estimated the long-term probability of a basaltic eruptionwith magmatic unrest in zone 5 (submarine area) occurringin the next 20 years to be 0.11± 0.04.

If we now look at the most likely scenarios that also in-clude size, hazard and the extent of the eruption, the five nextmost likely scenarios are basaltic eruptions of VEI 2 withmagmatic unrest that generate short lava flows. However, inthis case zone 2 is no longer among the 5 most likely scenar-ios and an eruption in zone 5 with a VEI of 1 or less becomesthe fifth most likely to occur in the next 20 years (probabil-ity of 0.01± 0.01). Once again, the standard deviation forthese estimates is large, implying that the variability due touncertainties in the input data is also large. In this case, weestimated that the most probable scenario (0.04± 0.02) is asubmarine (zone 5) mafic magmatic eruption of VEI 2 gen-erating short lava flows.

9 Eruptive scenarios

Hazard assessment must be based on the simulation ofdifferent volcanic processes across the susceptibility map(e.g. Martí et al., 2012). In order to illustrate potential fu-ture eruptions on El Hierro, we simulated scenarios assum-ing the results obtained with HASSET and considering themost probable hazards (i.e. lava flows, fallout and PDCs) thatcould occur in the event of such eruptions. We mainly con-sidered eruptions that occur on land or in shallow submarineenvironments (at a depth of less than 200 m) (Fig. 3). We didnot consider deeper submarine eruptions even though theirsocio-economic impact may in fact not be negligible, as seenin the 2011–2012 eruption. However, we assumed that thedirect impact of hazards caused by these deeper submarineeruptions on the island was not relevant for the purpose ofthis study.

For the simulations we used light detection and ranging(LIDAR) technology based on the digital elevation model(DEM) of the island with a cell size of 10 m generated bythe National Geographic Institute (IGN).

10 Lava flow scenarios

Bearing in mind the previously obtained susceptibility val-ues (Fig. 2) (Becerril et al., 2013), we simulated lava flow



Table 3. (a) Most likely scenarios for node location. (b) Most likely scenarios for node extent.

Scenario Probability Standardestimate deviation

(a)

1. Yes-magmatic-magmatic eruption-Zone 5 0.11 0.04





(b)

1. Basaltic eruption with magmatic unrest in zone 5, 0.04 0.02VEI 2, that generates lava flows of short extent




5. Basaltic eruption with magmatic unrest in zone 5, 0.01 0.01VEI ≤ 1, that generates lava flows of short extent

Figure 4. Lava flow scenarios for El Hierro performed withVORIS 2.0.1. Vents from lava flows that have been simulated rep-resent those with the highest spatial probabilities (see susceptibilitymap in Fig. 2). Red colours are those areas with the highest proba-bility to be invaded by lava flows.

scenarios taking into account only those pixels located onland (lava flows generated in submarine eruptions, even inshallow waters, were assumed not to cause any direct impacton the island). Lava flow simulations based on VORIS 2.0.1rely on a probabilistic model that assumes that topographyis the most important factor in determining the path of alava flow (Felpeto et al., 2007 and references therein). As

explained before, simulations of lava flows were conductedon land and are based on the pixels that lie on the differentspatial probability values ranging from 0.00037 to 0.0068.

In the model, the input parameters for the lava flows wereconstrained by maximum flow lengths and thicknesses takenfrom field measurements. Considering that most lava flows inthe past reached the sea, we assumed flow lengths of about15 km. The thickness used as input for the models was 3 m,which was obtained from the average value of individualflows measured in the field. The results provide a map thatgives the probability that any particular cell is invaded by alava flow (Fig. 4).

11 Scenarios for pyroclastic density currents (PDCs)

The pyroclastic density currents (PDCs) identified on ElHierro are all associated with hydrovolcanic episodes andmostly relate to mafic vents located in the coastal zone, orepisodes occurring at shallow submarine depths that gener-ated deposits that are now exposed along the coast. However,we also considered the possibility that this type of explosiveepisode could occur on land with more evolved composi-tions and larger run-out distances, as is the case of the Mal-paso member identified in the centre of the island (Pedrazziet al., 2014). PDCs were simulated with an energy conemodel (Sheridan and Malin, 1983) using as input parame-ters topography, the collapse equivalent height (H) and thecollapse equivalent angle (θ ), which is obtained through the



arctangent of the ratio betweenHc andL, whereL representsthe run-out length (Felpeto et al., 2007; Toyos et al., 2007).Run-out distances were considered to be equivalent to themost distal exposure of PDC deposits found on the island,which were calculated to have lengths of 5, 1 and 0.5 km.These distances are relative to the most distal deposits of thestudied PDCs.

Collapse equivalent heights were chosen in the range of250–300 m above the possible vent site in order to constrainthe best Hc that matches real deposits. Based on the cali-bration, a collapse equivalent of 250 and an angle of 11◦

were determined for a pyroclastic flow deposit, resemblingthe known Malpaso member felsic flow deposit. For thosevents located in the coastal zone or associated with maficeruptions, we simulated PDCs with a collapse equivalent of250 m and angles in the range of around 4–27◦ (low valuesfor base surge explosions and high values for column col-lapse phases) (Sheridan and Malin, 1983). Although the to-pography of the area has been modified since the eruptionof the Malpaso member, the area and extent of the simu-lated deposits were still similar to the real PDC deposit. Withthese constraints, PDC simulations were carried out in the ar-eas with the highest spatial probabilities (Fig. 5a). The areasclose to the PDC deposits of El Hierro were also selected tosimulate scenarios (Fig. 5b). Figure 5a and b show coverageareas with different Heim coefficients and VEI values.

12 Fallout

Fallout from the eruptions on El Hierro was simulated byassuming a violent Strombolian eruption (e.g. Tanganasogaeruption, Fig. 1), characterised by the formation of an erup-tive column up to 10 km high (Arrighi et al., 2001), havingsignificant impacts over distances of several tens of kilome-tres from the vent (Valentine and Gregg, 2008), which wouldrepresent one of the most probable high intensity eruptionsthat could occur on the island. Nevertheless, we do not ruleout the possibility of a subplinian eruption, characterised bycolumns ranging between 10 and 20 km altitude, having po-tential impacts over much larger regions and even globally(Valentine and Gregg, 2008 and references therein) in theevent that more felsic magmas are involved in the process.Simulations were conducted using an advection-diffusionmodel based on the assumption that particle motion is con-trolled by advection from wind, particle diffusion and theirterminal settling velocity (Pfeiffer et al., 2005; Felpeto et al.,2007). All the simulations were conducted with one vent lo-cated in the highest spatial probability area and another onthe eastern side of the island, the most vulnerable area for avolcanic event and where the main villages, airport and portare situated.

Data inputs of wind profiles were compiled from theUniversity of Wyoming Department of Atmospheric Sci-ence sounding database (http://weather.uwyo.edu/upperair/

Figure 5. PDC scenarios performed with VORIS 2.0.1. Covered ar-eas with different collapse equivalent heights (Hc), collapse equiv-alent angles (θ ) and VEI values (see the text for more detail).(a) VEI 2 corresponding to felsic eruptions;(b) VEI 1 correspond-ing to mafic eruptions.

sounding.html). We focused the attention of our study onthe fallout scenarios for the average wind value of eachseason during the last decade. Wind direction and intensitywere chosen at different vertical heights (500, 1000, 2000,4000 and 6000 m).

Input parameters for the simulation were obtained fromfieldwork and bibliographic data. Results are shown in Fig. 6,with particle distribution in a 5 km high eruptive column re-lated to a violent Strombolian eruption, generating 0.03 km3

of deposits. Particle sizes were considered in a range from−6 to 28, thereby covering the entire range of particle sizesobserved in the field.


http://weather.uwyo.edu/upperair/sounding.html

http://weather.uwyo.edu/upperair/sounding.html


Figure 6. Ashfall scenarios from a violent Strombolian eruptionperformed with VORIS 2.0.1. (1) Simulation at the highest proba-bility vent; (2) simulation at an area close the main areas of popula-tion. Both simulations were performed for summer, autumn, winterand spring.

13 Total hazard map

Combination of the most probable scenarios related tobasaltic eruptions of VEI 2 that generate lava flows, falloutand PDCs in case of hydrovolcanic events, provided the firsttotal qualitative volcanic hazard map of El Hierro (Fig. 7b).The most probable areas to be affected by the three mostlikely scenarios were used to define the areas with the great-est and lowest overall volcanic hazard (Fig. 7b). This is anapproach similar to that taken by Lindsay et al. (2005) inthe Lesser Antilles. We distinguished four levels of hazarddepending on the number of individual hazards (Fig. 7a)that overlap on each point (pixel) of the map. The superpo-sition was done taking into account the spatial probabilityand the extension of each scenario, given more weight to themost probable scenario, i.e. lava flows originating from ar-eas with high spatial vent opening probability. The resulting

Figure 7. (a) Superposition of the most probable scenarios;(b) qualitative hazard map of El Hierro (zones 1–4) constructedfrom the combination of the most likely scenarios. This map showsthe overall integrated volcanic hazard zones for El Hierro based onlava flows, PDCs and ashfall scenarios. We distinguish four levelsof hazard, from very low to high hazard, depending on the numberof individual hazards that overlap on each point (pixel) of the map(see text for more explanation).

map shows that, although El Hierro is not a highly populatedisland, some medium- and high-volcanic-hazard zones coin-cide with some of the main inhabited areas. However, it mustbe noted that this hazard level delineation is reliant on thecurrent information, which may be subject to further revisionthus implying possible changes in the hazard assessment.

14 Discussion and conclusions

Mafic monogenetic eruptions (Table 1) are the most commoneruption type to have occurred in El Hierro’s recent geologi-cal past, especially over the last 158 ka (Pellicer, 1977, 1979).Consequently, we assume that they also represent the mostlikely eruption types in the near future. These eruptions gen-erated small-size cones, lava flows, proximal scoria, fallout



and, occasionally, PDCs. The size of most of these erup-tions ranged from typical Strombolian to violent Strombo-lian (some of them associated with hydrovolcanic phases).In Fig. 7a the most likely expected scenarios on the islandare represented together. The presence of a relatively recenteruption of phonolitic composition of medium size calledMalpaso member and described as a PDC (Pedrazzi et al.,2014) is also remarkable, as it opens up the possibility thateruptions other than monogenetic magmatic and/or hydro-volcanic mafic ones may also occur on El Hierro. Althoughassociated with much greater hazard intensities, this type oferuption has a much lower probability of occurrence.

The catalogue of eruptions that have occurred on El Hi-erro in the last 158 ka is far from complete. This is evidentwhen trying to establish the relative stratigraphy of volcanicdeposits, as there are a large number of units of known ori-gin intercalated between the reported units. Although the es-tablishment of a complete volcano-stratigraphy of El Hierro(and, in particular, of its last constructive episode) is still re-quired, the available number of reported eruptions (for whichthe corresponding geochronology based on radiometric dat-ing exists) is large enough to provide a preliminary volcanichazard assessment with a sufficient degree of confidence.

The application of available tools such as HASSET(Sobradelo et al., 2014a) and VORIS 2.0.1 (Felpeto et al.,2007), specifically designed to undertake volcanic hazard as-sessment based on current knowledge of past eruptive activ-ity and using probabilistic methods and simulation models,allows us to obtain an initial long-term hazard assessment,which can be easily updated and improved with the incorpo-ration of new information such as a more complete volcano-stratigraphy and geochronology. This is an essential tool thatshould enable local authorities to apply more rational territo-rial planning and to design more adequate emergency plansto face future volcanic crises. The experience gained fromthe last eruption on El Hierro in 2011–2012 showed that thelack of tools such as the one described in the present studycan lead scientific advisors and decision-makers to considerpossible eruptive scenarios that have a very low probabilityof occurrence, whilst ignoring others with a high probabilityof occurrence – for example, the submarine eruption that inthe end turned out to be the true scenario. This lack of anysystematic study of past eruptive activity hampered the fore-casting of the most probable scenarios and led to a certainconfusion regarding the potential outcome of the impend-ing eruption. This in turn affected the way in which infor-mation was transmitted to the population and to the scale ofthe decisions made, some of which were unnecessarily over-protective (Sobradelo et al., 2014b).

The advantage of conducting a probabilistic hazard assess-ment is that the results obtained can be updated whenevernew information becomes available. Such an approach per-mits work to start even when only a little information ex-ists and then enables results to improve over time. Thus, ap-propriate mitigation policies can be based on less, but more

precise and realistic information. In the case of El Hierro, de-spite sufficient knowledge of past eruptive activity, the avail-able information was not structured in a comprehensive waythat was easy to manage and be used by decision-makersor even by the scientists who were providing advice. Theresults obtained in the present study, that is, the develop-ment of a probabilistic long-term volcanic hazard assessmentthat includes dynamic scenarios and a qualitative hazard map(Fig. 7a and b), offer basis on which to build the strategiesthat are required to successfully face up to and minimise theimpact of future volcanic eruptions on the island.

Our approach offers a method that facilitates accomplish-ing volcanic hazard assessment in a homogeneous and sys-tematic way. The approach is based on the history of the vol-cano being deduced from the geological record, which al-lows determining how, where, and when the next eruptioncould be. Similar approaches have been applied in other vol-canic areas where the application of available tools similarto ours have also allowed us to obtain an initial long-termhazard assessment. This is the case of Auckland VolcanicField in New Zealand (Sandri et al., 2012) or Misti volcanoin Peru (Sandri et al., 2014), where a Bayesian approach us-ing BET_VH tool (Marzocchi et al., 2010) and other simu-lation tools are applied to compute the temporal and spatialprobabilities. Our methodology uses different free tools thathave been developed to contribute to the long-term hazard as-sessment, both in spatial (VORIS 2.0.1, Felpeto et al., 2007)and temporal analyses (HASSET, Sobradelo et al., 2014a).The main advantage of using VORIS 2.0.1 is that it createsscenarios of different kind of hazards such as lava flows,PDCs and ashfall. Other works have focused on the simula-tion of only one scenario using non-free tools (e.g. lava flowsfor Etna volcano: Cappello et al., 2010, 2011; Tarquini andFavalli, 2010). On the other hand, although some parts of theHASSET tool (that evaluate temporal probabilities) coincidewith BET_EF and BET_VH tools presented by Marzocchi etal. (2008, 2010), HASSET is built on a Quantum Gis (QGIS)platform and considers different kinds of unrest episodes(seismic, geothermal, others), and moreover takes into ac-count the kind of outcome (e.g. phreatic explosion and sectorfailure) and the magma composition, overcoming the limita-tions of previous event tree models (Sobradelo et al., 2014a).Another important advantage of using these tools is that newdata or new model results can be easily included in the pro-cedure to update the hazard assessment. Other works focusedon the evaluation of the potential hazards related to a specifickind of hazard of a particular area (e.g. phreatomagmatic vol-canic hazards; Németh and Cronin, 2011) could take the ad-vantages of our methodology and implement it in an easyand successful way for future and completeness of volcanichazard evaluation.



Acknowledgements.This research was partially funded byIGME, CSIC and the European Commission (FT7 Theme:ENV.2011.1.3.3-1; Grant 282759: “VUELCO”), and MINECOgrant CGL2011-16144-E. We would like to thank X. Bolós andJ. P. Galve for their help in the development of figures. We alsowant to thank J. Lindlay and K. Németh for their very usefulsuggestions that have enabled us to significantly improve ourmanuscript. The English text was corrected by Michael Lockwood.

Edited by: A. CostaReviewed by: J. Lindsay and K. Németh

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